1. An underwater sensor data collection method, comprising the steps of:

acquiring M-1 underwater acoustic signals, wherein the underwater acoustic signals are acquired through a circular array arranged on an underwater autonomous vehicle, the circular array is composed of M array elements, and the underwater acoustic signals are noise signals or underwater acoustic beacons sent by sensor nodes; acquiring K underwater sound beacons from the M-1 underwater sound signals according to the power of the underwater sound signals, and calculating the detection probability of the sensor nodes corresponding to the underwater sound beacons;

acquiring azimuth angles corresponding to the underwater acoustic beacons, grouping sensor nodes corresponding to the K underwater acoustic beacons according to the azimuth angles, grouping the sensor nodes of which the underwater autonomous vehicle can collect node data in the same navigation track into a group, and acquiring the cruise direction corresponding to each group;

and calculating the data collection efficiency of each group according to the detection probability, controlling the underwater autonomous vehicle to move according to the cruising direction of the group corresponding to the maximum data collection efficiency, and collecting sensor data.

2. The method of claim 1, wherein the sensor node broadcasts periodically an underwater acoustic beacon when the buffer memory reaches B bytes; and keeping silent when the cache does not reach the B bytes.

3. The method for collecting the data of the underwater sensor according to claim 1, wherein the acquiring K underwater acoustic beacons from M-1 underwater acoustic signals according to the power of the underwater acoustic signals and calculating the detection probability of the sensor node corresponding to the underwater acoustic beacon comprises:

judging whether the underwater sound signal is an underwater sound beacon or a noise signal according to the power of the underwater sound signal and a preset judgment mode;

if the underwater sound beacon is the underwater sound beacon, the sensor node corresponding to the underwater sound beacon is placed into a detection node setCalculating the detection probability of the sensor node;

assume that the power is represented as:

the expression of the detection probability is:

wherein σ²As variance of noise, p_kIs the received signal power; after calculation, when H is made₁When the underwater sound beacon is judged, the underwater sound beacon is represented as an underwater sound beacon; when making H₀When the underwater sound beacon is judged, the underwater sound beacon is represented as a noise signal; t(s)_k) To test statistic, γ'₀In order to decide the threshold value, the threshold value is determined,is a random variable conforming to a chi-square distributionThe right tail of (1) is distributed; placing detected sensor nodes into a set of detection nodesIn (1).

4. The method of claim 3, wherein the determining the underwater acoustic signal by using the likelihood ratio hypothesis test comprises:

at H₀(k) In (1), the received signal obeys s_k～N(0,σ²) (ii) a At H₁(k) In (1), the received signal obeys s_k～N(0,(M-1)p_k+σ²) (ii) a The likelihood ratio hypothesis test decisions are as follows:

wherein N is the number of fast rows,to predict the incident signal, γ'₀Is a decision threshold.

5. The method for collecting data from an underwater sensor as claimed in claim 1, wherein said obtaining an azimuth angle corresponding to the underwater acoustic beacon comprises:

analyzing the M-1 underwater acoustic signals by adopting an MUSIC algorithm to obtain an MUSIC spatial spectrum, and acquiring azimuth angles corresponding to the M-1 underwater acoustic signals according to the maximum M-1 peak;

acquiring azimuth angles corresponding to the underwater acoustic beacons from the azimuth angles corresponding to the M-1 underwater acoustic signals;

wherein, the expression of the MUSIC algorithm is as follows:

wherein A is an array manifold matrix of a circular array, U_NRepresenting a noise subspace.

6. The method of claim 1, wherein the sensor nodes corresponding to the K underwater acoustic beacons are grouped as follows:

the azimuth angles of any two sensor nodes in the K sensor nodes areAndif the azimuth angles of the two sensor nodes satisfy:

grouping two sensor nodes into a group G_j(ii) a If the plurality of sensor nodes mutually meet the condition, the plurality of sensor nodes are divided into a group;

for any group G_jThe cruising direction for collecting the set of data is

Wherein the content of the first and second substances,

c represents the maximum communication distance of the sensor node, and D represents the maximum detection distance of the underwater autonomous vehicle.

7. The method of claim 1, further comprising the step of blind spot detection, comprising:

under the condition that the underwater autonomous vehicle cannot acquire the underwater acoustic beacon, the underwater autonomous vehicle moves by adopting a random walk method until the underwater acoustic beacon is acquired;

the calculation formula of the data collection efficiency is as follows:

wherein B is the size of the data packet,in order to detect the probability for a node,represents the energy loss of the autonomous underwater vehicle,set representing grouping result of this time

8. An underwater sensor data collection system, comprising:

the underwater acoustic signal acquisition module is used for acquiring M-1 underwater acoustic signals, wherein the underwater acoustic signals are acquired through a circular array arranged on an underwater autonomous vehicle, the circular array is composed of M array elements, and the underwater acoustic signals are noise signals or underwater acoustic beacons sent by sensor nodes;

the signal selection module is used for acquiring K underwater sound beacons from the M-1 underwater sound signals according to the power of the underwater sound signals and calculating the detection probability of the sensor nodes corresponding to the underwater sound beacons;

the node grouping module is used for acquiring azimuth angles corresponding to the underwater acoustic beacons, grouping the sensor nodes corresponding to the K underwater acoustic beacons according to the azimuth angles, grouping the sensor nodes of which the underwater autonomous vehicle can collect node data in the same navigation track into a group, and acquiring the cruise direction corresponding to each group;

and the data acquisition module is used for calculating the data collection efficiency of each group according to the detection probability, controlling the underwater autonomous vehicle to move according to the cruise direction of the group corresponding to the maximum data collection efficiency and acquiring sensor data.

9. An underwater sensor data collection device, comprising:

at least one processor;

at least one memory for storing at least one program;

when executed by the at least one processor, cause the at least one processor to implement the method of any one of claims 1-7.

10. A storage medium having stored therein a program executable by a processor, wherein the program executable by the processor is adapted to perform the method of any one of claims 1-7 when executed by the processor.

Background

In an underwater sensor node using a battery as an energy source, a large amount of energy is consumed for data collection by adopting long-distance underwater acoustic communication. The underwater autonomous vehicle can move to a place close to the sensor node to collect data, and the data are collected by using a low-energy-consumption, close-range and high-speed communication mode. The energy consumption of the underwater sensor node can be reduced by using the underwater autonomous vehicle to collect data, which is very important for the battery-driven underwater sensor node.

Many studies on data collection schemes of the underwater autonomous vehicle aim at a scene that the node position is known, and in the scene, the data collection track of the underwater autonomous vehicle can be carefully calculated according to the node position before the underwater autonomous vehicle is deployed. However, in some practical applications, the location of the underwater sensor nodes is unknown. In such a situation, a completely new dynamic planning is needed to achieve data collection for the autonomous underwater vehicle.

Disclosure of Invention

In order to solve at least one of the technical problems in the prior art to a certain extent, the invention aims to provide a method, a system, a device and a medium for dynamically collecting data by using an autonomous underwater vehicle based on detection under the condition that the position of an underwater sensor node is unknown.

The technical scheme adopted by the invention is as follows:

an underwater sensor data collection method comprising the steps of:

acquiring M-1 underwater acoustic signals, wherein the underwater acoustic signals are acquired through a circular array arranged on an underwater autonomous vehicle, the circular array is composed of M array elements, and the underwater acoustic signals are noise signals or underwater acoustic beacons sent by sensor nodes;

acquiring K underwater sound beacons from the M-1 underwater sound signals according to the power of the underwater sound signals, and calculating the detection probability of the sensor nodes corresponding to the underwater sound beacons;

acquiring azimuth angles corresponding to the underwater acoustic beacons, grouping sensor nodes corresponding to the K underwater acoustic beacons according to the azimuth angles, grouping the sensor nodes of which the underwater autonomous vehicle can collect node data in the same navigation track into a group, and acquiring the cruise direction corresponding to each group;

and calculating the data collection efficiency of each group according to the detection probability, controlling the underwater autonomous vehicle to move according to the cruising direction of the group corresponding to the maximum data collection efficiency, and collecting sensor data.

Further, when the cache reaches B bytes, the sensor node periodically broadcasts an underwater sound beacon; and keeping silent when the cache does not reach the B bytes.

Further, the acquiring K underwater acoustic beacons from M-1 underwater acoustic signals according to the power of the underwater acoustic signals and calculating the detection probability of the sensor node corresponding to the underwater acoustic beacon include:

judging whether the underwater sound signal is an underwater sound beacon or a noise signal according to the power of the underwater sound signal and a preset judgment mode;

if the underwater sound beacon is the underwater sound beacon, the sensor node corresponding to the underwater sound beacon is placed into a detection node setCalculating the detection probability of the sensor node;

assume that the power is represented as:

the expression of the detection probability is:

wherein σ²As variance of noise, p_kIs the received signal power; after calculation, when H is made₁Decision makingWhen the signal is received, the underwater sound beacon is an underwater sound beacon; when making H₀When the underwater sound beacon is judged, the underwater sound beacon is represented as a noise signal; t(s)_k) To test statistic, γ'₀In order to decide the threshold value, the threshold value is determined,is a random variable conforming to a chi-square distributionThe right tail of (1) is distributed; placing detected sensor nodes into a set of detection nodesIn (1).

Further, the method for judging the underwater sound signal by adopting the likelihood ratio hypothesis test comprises the following steps:

at H₀(k) In (1), the received signal obeys s_k～N(0,σ²) (ii) a At H₁(k) In (1), the received signal obeys s_k～N(0,(M-1)p_k+σ²) (ii) a The likelihood ratio hypothesis test decisions are as follows:

wherein N is the number of fast rows,to predict the incident signal, γ'₀Is a decision threshold.

Further, the obtaining of the azimuth corresponding to the underwater acoustic beacon includes:

analyzing the M-1 underwater acoustic signals by adopting an MUSIC algorithm to obtain an MUSIC spatial spectrum, and acquiring azimuth angles corresponding to the M-1 underwater acoustic signals according to the maximum M-1 peak;

acquiring azimuth angles corresponding to the underwater acoustic beacons from the azimuth angles corresponding to the M-1 underwater acoustic signals;

wherein, the expression of the MUSIC algorithm is as follows:

wherein A is an array manifold matrix of a circular array, U_NRepresenting a noise subspace.

Further, grouping the sensor nodes corresponding to the K underwater acoustic beacons according to the following mode:

the azimuth angles of any two sensor nodes in the K sensor nodes areAndif the azimuth angles of the two sensor nodes satisfy:

grouping two sensor nodes into a group G_j(ii) a If the plurality of sensor nodes mutually meet the condition, the plurality of sensor nodes are divided into a group;

for any group G_jThe cruising direction for collecting the set of data is

Wherein the content of the first and second substances,

c represents the maximum communication distance of the sensor node, and D represents the maximum detection distance of the underwater autonomous vehicle.

Further, the underwater sensor data collection method further comprises a blind area detection step, including:

under the condition that the underwater autonomous vehicle cannot acquire the underwater acoustic beacon, the underwater autonomous vehicle moves by adopting a random walk method until the underwater acoustic beacon is acquired;

the calculation formula of the data collection efficiency is as follows:

wherein B is the size of the data packet,in order to detect the probability for a node,represents the energy loss of the autonomous underwater vehicle,set representing grouping result of this time

The other technical scheme adopted by the invention is as follows:

an underwater sensor data collection system comprising:

the underwater acoustic signal acquisition module is used for acquiring M-1 underwater acoustic signals, wherein the underwater acoustic signals are acquired through a circular array arranged on an underwater autonomous vehicle, the circular array is composed of M array elements, and the underwater acoustic signals are noise signals or underwater acoustic beacons sent by sensor nodes;

the signal selection module is used for acquiring K underwater sound beacons from the M-1 underwater sound signals according to the power of the underwater sound signals and calculating the detection probability of the sensor nodes corresponding to the underwater sound beacons;

the node grouping module is used for acquiring azimuth angles corresponding to the underwater acoustic beacons, grouping the sensor nodes corresponding to the K underwater acoustic beacons according to the azimuth angles, grouping the sensor nodes of which the underwater autonomous vehicle can collect node data in the same navigation track into a group, and acquiring the cruise direction corresponding to each group;

and the data acquisition module is used for calculating the data collection efficiency of each group according to the detection probability, controlling the underwater autonomous vehicle to move according to the cruise direction of the group corresponding to the maximum data collection efficiency and acquiring sensor data.

The other technical scheme adopted by the invention is as follows:

an underwater sensor data collection device comprising:

at least one processor;

at least one memory for storing at least one program;

when executed by the at least one processor, cause the at least one processor to implement the method described above.

The other technical scheme adopted by the invention is as follows:

a storage medium having stored therein a processor-executable program for performing the method as described above when executed by a processor.

The invention has the beneficial effects that: the invention adopts the circular array to detect the direction of the node, so that the underwater autonomous vehicle can collect data under the condition that the position of the node is unknown.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description is made on the drawings of the embodiments of the present invention or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.

FIG. 1 is a schematic diagram of an autonomous underwater vehicle detecting a node in an embodiment of the invention;

FIG. 2 is a diagram of a packet model in an embodiment of the invention;

FIG. 3 is a diagram illustrating grouping results according to an embodiment of the present invention;

fig. 4 is a flowchart of a method for probe-based autonomous underwater vehicle dynamic data collection in an embodiment of the present invention.

Detailed Description

Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention. The step numbers in the following embodiments are provided only for convenience of illustration, the order between the steps is not limited at all, and the execution order of each step in the embodiments can be adapted according to the understanding of those skilled in the art.

In the description of the present invention, it should be understood that the orientation or positional relationship referred to in the description of the orientation, such as the upper, lower, front, rear, left, right, etc., is based on the orientation or positional relationship shown in the drawings, and is only for convenience of description and simplification of description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention.

In the description of the present invention, the meaning of a plurality of means is one or more, the meaning of a plurality of means is two or more, and larger, smaller, larger, etc. are understood as excluding the number, and larger, smaller, inner, etc. are understood as including the number. If the first and second are described for the purpose of distinguishing technical features, they are not to be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated or implicitly indicating the precedence of the technical features indicated.

In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.

As shown in fig. 4, the present embodiment discloses a method for collecting dynamic data of an underwater autonomous vehicle based on detection, which can be executed by a controller arranged on the underwater autonomous vehicle, and comprises the following steps:

and S1, receiving array signals.

The circular array receives M-1 incident signal sources, the first K incident signals represent real signal sources, the last M-1-K incident signals represent virtual signal sources generated by noise, and the array received signals can be represented as:

wherein, a_kIs an array direction vector, s_k(t) denotes a received signal, n (t) is noise; in the present embodiment, the underwater acoustic beacon is detected by using a circular array with an array element number of 16, that is, M is 16.

The circular array is arranged on the underwater autonomous vehicle and consists of M array elements. The circular array detects the underwater acoustic beacon and adjusts the motion direction in real time according to the detection result.

The real signal source is sent out by an underwater sensor node, the sensor node continuously senses and stores sensed data in a data cache region, and an underwater sound beacon is periodically broadcast when the cache reaches B bytes; otherwise, the sensor transceiver will remain silent to save energy. In this embodiment, as shown in fig. 1, there are m underwater sensor nodes in the network. Wherein n sensor nodes have transmitted data to the underwater autonomous vehicle, the n sensor nodes will empty the data buffer, start a new sensing round, and keep the transceiver silent to save energy. The data cache of the rest m-n sensor nodes reaches B bytes and broadcasts the underwater sound beacon periodically.

And S2, estimating the node direction.

Calculating and analyzing the received signals by using a MUSIC algorithm, and estimating azimuth angles of M-1 signal sources (including real signal sources and virtual signal sources); in the present embodiment, the signal direction is estimated by using the MUSIC algorithm, and the MUSIC power spectrum can be expressed as:

wherein A is an array manifold matrix of a circular array, U_NRepresenting a noise subspace. According to the obtained MUSIC space spectrum, the direction of M-1 signals can be estimated by selecting the largest M-1 peak

And S3, node existence estimation and detection probability calculation.

Using a power hypothesis test to distinguish whether M-1 signal sources in the estimate S2 are from nodes or virtual signals, the power hypothesis can be expressed as:

wherein σ²As variance of noise, p_kIs the received signal power; after calculation, when H is made₁When judging, the direction signal comes from the node; when making H₀When judging, the direction is a virtual signal. And the probability of detection of this direction can be expressed as:

wherein, T(s)_k) To test statistic, γ'₀In order to decide the threshold value, the threshold value is determined,is a random variable conforming to a chi-square distributionThe right tail of (1) is distributed; placing the detected nodes into a set of detected nodesPerforming the following steps; in this embodiment, the signal is decided using likelihood ratio hypothesis testing, as follows: at H₀(k) In (1), the received signal obeys s_k～N(0,σ²) (ii) a At H₁(k) In (1), the received signal obeys s_k～N(0,(M-1)p_k+σ²) (ii) a The likelihood ratio hypothesis test decisions are as follows:

wherein N is the number of fast rows,to predict the incident signal, γ'₀Is a decision threshold; when making H₁When judging, the direction signal comes from the node; when making H₀When judging, the direction is a virtual signal; finally, g detected nodes are put into a detection node setIn (1).

And S4, grouping the detected sensor nodes.

Dividing the nodes of which the autonomous underwater vehicle can collect node data in the same navigation track into nodes by using the node orientations detected in the S3One group, denoted as G_jAnd calculating the cruising direction for collecting the data;

s41, grouping rule:

for two angle estimates in the probe node setAndif their angle satisfies

Then divide them into a group G_j(ii) a If the plurality of nodes mutually meet the condition, the nodes are also divided into a group; in this embodiment, as shown in fig. 2(a) and fig. 2(B), the autonomous underwater vehicle can collect data of nodes a and B in the same cruise track, and can group A, B nodes into one group, that is:

packet computation rules as shown in fig. 2(c), two points a 'and B' are grouped together assuming that they have a common communication area at the edge of the detection area, namely:

wherein C represents the maximum communication distance of the sensor node, and D represents the maximum detection distance of the underwater autonomous vehicle.

S42, calculating the cruising direction:

for arbitrary packets G_jThe cruising direction for collecting the set of data is

In the present embodiment, as shown in fig. 2, the cruising direction for collecting the set of dataComprises the following steps:

and S5, selecting a group to be accessed next by the underwater autonomous cruise device.

The underwater autonomous cruise controller selects one of the plurality of groupings generated at S4 (denoted as the grouping having the greatest data collection efficiency)) As a packet to be accessed next, that is, the packet satisfies the following condition,

wherein B is the size of the data packet,in order to detect the probability for a node,represents the energy loss of the autonomous underwater vehicle,set representing grouping result of this timeIn this embodiment, as shown in figure 3,the autonomous underwater vehicle needs to select the one with the maximum data collection efficiency among 3 groups according to a risk-benefit modelAccess is performed.

In step S5, the group that can obtain the maximum data collection efficiency is selectedWill simultaneously take into account the expected collected data and its risk of error, the energy loss of the underwater autonomous vehicle, and the risk of other group node data loss.

And S6, detecting the blind area to escape.

Under the condition that the node cannot be detected, the cruising direction of the next step cannot be determined through S5, and the underwater autonomous vehicle enters a detection blind area; at the moment, the autonomous underwater vehicle moves by adopting a random walk method until escaping from a detection blind area; in this embodiment, if the underwater autonomous vehicle enters an area where no node is detected during the dynamic cruise process, the underwater autonomous vehicle randomly selects a direction and cruises for a certain distance along the direction, and if a node is detected during the cruise process, the process immediately proceeds to step S4; if no node is detected during cruising in the direction for a certain distance, the underwater autonomous vehicle will go to step S6 again to reselect a random direction for the next cruising.

In step S6, a situation that the underwater autonomous vehicle may enter a detection blind area during the dynamic cruise process is considered, and no node is detected by the underwater autonomous vehicle in the detection blind area. In this case, the autonomous underwater vehicle randomly selects a direction and cruises for a certain distance along the direction, and if a node is detected during the crusing process, the step S4 is immediately performed; if no node is detected during cruising in the direction for a certain distance, the underwater autonomous vehicle will go to step S6 again to reselect a random direction for the next cruising.

S7, collecting the data of the surrounding nodes while the underwater autonomous vehicle sails along the direction determined by the S5 or the S6, stopping cruising and returning to the S1 to restart the detection after collecting the data amount to be collected by the group, and collecting the detection node setResetting is carried out in a zero clearing mode, and the process is circulated until the energy of the underwater autonomous vehicle is reduced to a certain threshold value or all node data are collected and then returned to the water surface; in this embodiment, ifIn which there are a nodes, the underwater autonomous vehicle followsThe direction cruise is carried out, after the data of a nodes are collected, the underwater autonomous vehicle stops cruising and returns to S1 to restart the detection, and the detection node setAnd also clears the reset accordingly.

In summary, compared with the prior art, the method of the embodiment has the following beneficial effects:

(1) in the embodiment, for the detection-based dynamic data collection method of the underwater autonomous vehicle, the direction of the node is detected by adopting the circular array, so that the underwater autonomous vehicle can collect data under the condition that the position of the node is unknown.

(2) In the embodiment, aiming at a detection-based dynamic data collection method of an underwater autonomous vehicle, the cruising energy consumption of the underwater autonomous vehicle in the data collection process is reduced by adopting a method of grouping detected nodes.

(3) In the embodiment, aiming at the detection-based dynamic data collection method of the underwater autonomous vehicle, a risk-benefit model is adopted, factors such as the detection risk and the cruising energy consumption of the underwater autonomous vehicle are considered, and a group with the maximum data collection efficiency is selected for collection, so that the collection efficiency of the underwater autonomous vehicle is effectively improved.

(4) In the embodiment, a random walk method is adopted for an underwater autonomous vehicle dynamic data collection method based on detection, a detection blind area is escaped, and the situation that the underwater autonomous vehicle cannot make a decision on how to perform the next step when a node cannot be detected is avoided.

The present embodiment also provides an underwater sensor data collection system, including:

the underwater acoustic signal acquisition module is used for acquiring M-1 underwater acoustic signals, wherein the underwater acoustic signals are acquired through a circular array arranged on an underwater autonomous vehicle, the circular array is composed of M array elements, and the underwater acoustic signals are noise signals or underwater acoustic beacons sent by sensor nodes;

the signal selection module is used for acquiring K underwater sound beacons from the M-1 underwater sound signals according to the power of the underwater sound signals and calculating the detection probability of the sensor nodes corresponding to the underwater sound beacons;

the node grouping module is used for acquiring azimuth angles corresponding to the underwater acoustic beacons, grouping the sensor nodes corresponding to the K underwater acoustic beacons according to the azimuth angles, grouping the sensor nodes of which the underwater autonomous vehicle can collect node data in the same navigation track into a group, and acquiring the cruise direction corresponding to each group;

and the data acquisition module is used for calculating the data collection efficiency of each group according to the detection probability, controlling the underwater autonomous vehicle to move according to the cruise direction of the group corresponding to the maximum data collection efficiency and acquiring sensor data.

The underwater sensor data collection system can execute the underwater sensor data collection method provided by the method embodiment of the invention, can execute any combination of the implementation steps of the method embodiment, and has corresponding functions and beneficial effects of the method.

The embodiment also provides an underwater sensor data collection device, including:

at least one processor;

at least one memory for storing at least one program;

when executed by the at least one processor, cause the at least one processor to implement the method as shown in fig. 4.

The underwater sensor data collection device can execute the underwater sensor data collection method provided by the method embodiment of the invention, can execute any combination of the implementation steps of the method embodiment, and has corresponding functions and beneficial effects of the method.

The embodiment of the application also discloses a computer program product or a computer program, which comprises computer instructions, and the computer instructions are stored in a computer readable storage medium. The computer instructions may be read by a processor of a computer device from a computer-readable storage medium, and executed by the processor to cause the computer device to perform the method illustrated in fig. 4.

The embodiment also provides a storage medium, which stores instructions or a program capable of executing the detection-based underwater autonomous vehicle dynamic data collection method provided by the method embodiment of the invention, and when the instructions or the program are executed, the steps can be executed by any combination of the method embodiments, and the corresponding functions and advantages of the method are achieved.

In alternative embodiments, the functions/acts noted in the block diagrams may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality/acts involved. Furthermore, the embodiments presented and described in the flow charts of the present invention are provided by way of example in order to provide a more thorough understanding of the technology. The disclosed methods are not limited to the operations and logic flows presented herein. Alternative embodiments are contemplated in which the order of various operations is changed and in which sub-operations described as part of larger operations are performed independently.

Furthermore, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise stated to the contrary, one or more of the described functions and/or features may be integrated in a single physical device and/or software module, or one or more functions and/or features may be implemented in a separate physical device or software module. It will also be appreciated that a detailed discussion of the actual implementation of each module is not necessary for an understanding of the present invention. Rather, the actual implementation of the various functional modules in the apparatus disclosed herein will be understood within the ordinary skill of an engineer, given the nature, function, and internal relationship of the modules. Accordingly, those skilled in the art can, using ordinary skill, practice the invention as set forth in the claims without undue experimentation. It is also to be understood that the specific concepts disclosed are merely illustrative of and not intended to limit the scope of the invention, which is defined by the appended claims and their full scope of equivalents.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.

The logic and/or steps represented in the flowcharts or otherwise described herein, e.g., an ordered listing of executable instructions that can be considered to implement logical functions, can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus, or device, such as a computer-based system, processor-containing system, or other system that can fetch the instructions from the instruction execution system, apparatus, or device and execute the instructions. For the purposes of this description, a "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device.

More specific examples (a non-exhaustive list) of the computer-readable medium would include the following: an electrical connection (electronic device) having one or more wires, a portable computer diskette (magnetic device), a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium could even be paper or another suitable medium upon which the program is printed, as the program can be electronically captured, via for instance optical scanning of the paper or other medium, then compiled, interpreted or otherwise processed in a suitable manner if necessary, and then stored in a computer memory.

It should be understood that portions of the present invention may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

In the foregoing description of the specification, reference to the description of "one embodiment/example," "another embodiment/example," or "certain embodiments/examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

While embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

While the preferred embodiments of the present invention have been illustrated and described, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.